Vetted Research Assistants

“Full-stack engineer with about 3 years of experience who is deeply hands-on with AI-assisted development and agentic systems. Built TubeAgent using LangChain, Ollama, FAISS, and Llama 3, and has demonstrated measurable impact by cutting review time by 90% and reducing deployment time from 30 minutes to under 5 minutes at NC State. Combines practical experimentation with strong architectural thinking around resilient, composable AI systems.”

“Built and owned core systems for VISTA, a VR drone training simulator in Unity/C#, including modular training scenarios, drone physics, restricted airspace logic, and dynamic weather-aware gameplay. Stands out for combining VR performance discipline on Meta Quest with realistic-yet-trainable flight controls and close collaboration with faculty SMEs to align the simulation with real training workflows.”

“Backend/full-stack engineer who has built AI-powered search and workflow systems in production, including a semantic resume-matching platform for recruiters and internal security data dashboards at ReliaQuest. Stands out for combining modern AI tooling with pragmatic reliability, performance tuning, and strong product intuition in ambiguous environments.”

“Unreal Engine 5 gameplay/systems developer who led major core features for the Early Access Steam city builder Geopogo Cities: Windsor Detroit, including an end-to-end building placement system tightly integrated with economy, AI pedestrians (Mass AI/Zone Graph/State Trees), and procedural city block generation. Also built a third-person exploration layer with character customization, stamina, and animation retargeting on top of the City Sample Crowd framework, plus shipped player-driven UX improvements based on live Early Access feedback.”

“Research-focused software engineer who builds performance-critical Python/C++ systems emphasizing correctness, state-transition precision, and distributed coordination. Created an automated simulation-based testing/validation framework for quantum programs that caught subtle logic/type errors early, reduced debugging time, and improved developer confidence through strong observability and scalable test generation.”

“Master’s-level IoT course project that the candidate helped evolve into a research lab effort by “ROSifying” a soil-fertility detection rover (autonomous navigation within a GPS geofence, sensor fusion, and rover-to-base-station telemetry via NRF24 to a Raspberry Pi dashboard). Also built a ROS/Gazebo vision-based teleoperation system using a SigLIP hand-gesture model mapped to geometry_msgs/Twist, and improved stability by instrumenting and filtering a latency-prone perception-to-control pipeline.”

“Robotics software engineer with internship experience at Lucid Motors building a mapping/localization pipeline that fuses LiDAR, camera, and GPS into high-fidelity 3D maps for autonomy/ADAS. Strong in SLAM and multi-robot systems—has modified ROS/ROS2 SLAM packages (FAST-LIO2, LIO-SAM) at the source level, optimized real-time multi-drone coordination for low-latency data sharing, and used Gazebo + Docker to simulate and deploy research robotics stacks.”

“Recent J&J intern who built a conversational RAG agent and led a shift from a monolithic model to a modular RAG workflow, cutting response time from several days to under a second by tackling data fragmentation, context retention, and embedding/latency optimization. Also worked on a large (7B-parameter) multimodal VQA pipeline for healthcare research and stays current via NeurIPS/ICLR and open-source contributions.”

varshini yaganti

Screened

Mid-level Data Analyst specializing in financial and customer analytics

Marietta, GA4y exp

“Analytics professional with experience at KPMG and Robosoft Technologies, working across financial and customer engagement data. They combine SQL, Python, experimentation, and BI dashboards to turn messy multi-source data into decision-ready insights, including a pricing test that improved conversion rates by 9%.”

“Full-stack product engineer who has owned complex internal platforms end-to-end, spanning React/TypeScript frontends, Flask/Redis backend systems, and relational data design. Particularly strong at turning technically dense workflows into intuitive user experiences, including a synthetic-imagery platform adopted by multiple Army research labs and a marketing analytics system with 99.99%+ uptime.”

Aswin Jojo

Screened

Junior Software Engineer specializing in full-stack development and machine learning

Houston, TX3y exp

“Full-stack engineer with experience owning products end-to-end in both insurtech/financial workflows and AI-enabled IT operations. Built scalable React/Node and FastAPI systems, improved reliability under peak transaction load with SQS/Redis, and shipped an AI ticket-classification platform that cut response times from 3 days to 1 day.”

“Data scientist with hands-on experience building an XGBoost-based customer segmentation/churn risk scoring model used by sales and marketing teams. Emphasizes production-grade practices—efficient SQL for large-scale data pulls, rigorous data validation/testing, and scalable, modular Python code designed to support multiple customer types.”

“Built and shipped production RAG-based LLM agents automating multi-step document query workflows, emphasizing reliability via monitoring, retries, structured exception handling, and fallback retrieval (alternative embeddings/keyword search). Demonstrated measurable gains (18% latency improvement, 25% retrieval efficiency, 12% precision) and has experience integrating agents with messy tax and transaction data at RSM using validation/cleaning and idempotent design.”

Shivani Sharma

Screened

Mid-Level Software Engineer specializing in Cloud, DevOps, and MLOps

Boston, MA3y exp

“Built and productionized a recommendation system from notebook prototype into a low-latency, scalable Cloud Run service using Docker, FastAPI, Terraform, CI/CD (GitHub Actions), and MLOps tooling (Vertex AI, MLflow). Experienced diagnosing real-time workflow issues using structured logging/ELK and GCP metrics, including resolving intermittent 504s by fixing unbounded SQL and adding caching. Also partners with sales/customer teams (Wasabi) to deliver tailored demos, troubleshoot, and drive onboarding/adoption.”

Dwarakesh Rajesh

Screened

Intern Robotics/Mechatronics Engineer specializing in automation and ROS2 systems

Boston, MA1y exp

“Robotics software builder who developed a solo fault-adaptive robotic arm: current-based joint health monitoring feeding an ESP32, ROS 2/MoveIt 2 motion planning that adapts to joint failures, and a custom brute-force IK solver to overcome URDF/MoveIt singularity issues. Also worked on real-time 12-microphone sensor-fusion audio processing for drone navigation, resolving buffer/noise problems with multithreading and chunked sampling; experienced with Webots/CoppeliaSim and learning Isaac Sim.”

Adhiraj Chadha

Screened

Junior Software Engineer specializing in AI, data, and full-stack applications

Amherst, MA3y exp

“Builder with a mix of backend engineering, product instinct, and startup execution: they shipped a legal BI platform from scratch that handled 1,000+ cases, cut reporting time 80%, and saved $30K annually. They also move quickly in ambiguous environments, from launching a roommate app across iOS/Android after user discovery to building a RAG system with a 50+ case evaluation suite and a cloud dev environment in under 48 hours.”

Stephen Pappachen

Screened

Director-level physician consultant specializing in clinical operations and healthcare administration

Lakeland, FL31y exp

“Clinician and former Center Medical Director with experience building operations from the ground up across OB/GYN practice and plasma donation settings. Brings a distinctive blend of clinical oversight, quality improvement, safety-focused implementation support, and protocol/algorithm authoring, especially in regulated healthcare environments.”

“Backend/full-stack engineer with deep experience building weather and geospatial data systems at WindBorne, spanning Next.js/TypeScript frontends through PostgreSQL, Redis, Sidekiq, Rails, Rust, and object-storage-backed forecast pipelines. Particularly strong in production reliability work—self-healing jobs, zero-downtime migrations, query/index optimization, and event-driven ingestion architectures that reduce latency and operational waste.”

“Founding member of Tausight, building AI systems to detect and protect PHI for healthcare organizations; helped take the company through post–Series A funding and exited after ~6 years. Drove a strategic collaboration with Intel’s OpenVINO team—becoming the first to deploy it in a real production system and improving model performance by ~30% on customer Intel-CPU machines.”

“Full-stack engineer and ML assistant in UC Irvine’s CS department who deployed a lab project showcase platform and integrated on-demand execution of computational projects using Docker for isolation. Also built and optimized Linux cloud/cluster test automation for research, diagnosing RAM and network sync bottlenecks, and later led development of a Python-based predictive analytics tool for musicians using probabilistic graphical models and flexible data pipelines.”

“QA automation engineer with hands-on ownership of Selenium (C#) and Cypress (JavaScript) suites, including CI integration in GitLab with PR smoke gating and nightly regressions with JUnit reports/screenshots. Drove a reported ~60% reduction in manual effort, improved suite maintainability through reuse/merging tests, and proactively shaped requirements/acceptance criteria in sprint planning to prevent defects (including claims calculation and server/log-related issues).”

Daniel Berhane Araya

Screened

Senior AI/ML Engineer specializing in production-grade LLM systems for regulated finance

Fairfax, VA9y exp

“AI/LLM engineer with published work who built FinVet, a production financial misinformation detection system using multi-pipeline RAG, confidence-based voting, and evidence-backed outputs (F1 0.85, +37% vs baseline). Also built NexusForest-MCP, a Dockerized Model Context Protocol server exposing structured global deforestation/carbon data via SQL tools for reliable LLM tool use. Previously delivered borrower risk-rating (PD) models at BMO Financial Group that were validated and integrated into an enterprise credit system through close collaboration with credit officers and portfolio managers.”

“Analytics professional with hands-on experience unifying marketing-platform data through Fivetran and Snowflake, building reporting views, and catching source-to-report issues like timezone-driven spend discrepancies. They also owned subscription LTV/cohort analysis and engagement tracking initiatives, partnering with e-commerce, product, and senior leadership to turn behavioral and demographic data into dashboards, lead-qualification metrics, and lifecycle marketing insights.”

Omkar Tulsidas Parab

Screened

Mid-level Software Engineer specializing in full-stack web and AI applications

United States5y exp

“Software engineer who owned an Order Management System end-to-end at Reliance Jio, improving large-table performance via UI virtualization shipped behind feature flags and refined through direct ops-user observation. Also built an OCR automation tool at Piramal Realty using Python/Tesseract with validation and manual correction fallbacks, driving adoption by operations teams. Experienced integrating with Kafka-based microservices and improving observability using structured logging and correlation IDs.”